• 한국전자통신학회논문지
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• 제7권6호
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• pp.1449-1454
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• 2012

수신 신호 세기 (RSSI: Received signal strength indicator)는 아날로그-디지털 변환기 입력단에서 수신신호의 세기를 나타낸다. 통신시스템에서 수신 신호 세기는 수신단에서 채널의 상태를 결정하는데 사용된다. 본 논문에서는 핸드오버상에서 실측값을 바탕으로 한 수신 신호 세기의 이용에 대해 알아본다. 먼저 WAVE (Wireless Access in Vehicular Environments)라 일컫어지는 차량통신을 위한 5.9GHz 주파수대에서 RSSI값을 측정한다. 측정된 데이터를 바탕으로 하여 빠른 핸드오버 방식 적용을 위한 수신 신호 세기의 이용에 대해 논의하고, 실제 고속도로 환경에서 RSSI를 이용하여 핸드오버를 적용한다.

• Journal of information and communication convergence engineering
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• 제9권6호
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• pp.676-682
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• 2011

Sybil attack can disrupt proper operations of wireless sensor network by forging its sensor node to multiple identities. To protect the sensor network from such an attack, a number of countermeasure methods based on RSSI (Received Signal Strength Indicator) and LQI (Link Quality Indicator) have been proposed. However, previous works on the Sybil attack detection do not consider the fact that Sybil nodes can change their RSSI and LQI strength for their malicious purposes. In this paper, we present a Sybil attack detection method based on a transmission power range. Our proposed method initially measures range of RSSI and LQI from sensor nodes, and then set the minimum, maximum and average RSSI and LQI strength value. After initialization, monitoring nodes request that each sensor node transmits data with different transmission power strengths. If the value measured by monitoring node is out of the range in transmission power strengths, the node is considered as a malicious node.

• Journal of Electrical Engineering and Technology
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• 제6권6호
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• pp.883-887
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• 2011

Location-based service (LBS) is becoming an important part of the information technology (IT) business. Localization is a core technology for LBS because LBS is based on the position of each device or user. In case of outdoor, GPS - which is used to determine the position of a moving user - is the dominant technology. As satellite signal cannot reach indoor, GPS cannot be used in indoor environment. Therefore, research and study about indoor localization technology, which has the same accuracy as an outdoor GPS, is needed for "seamless LBS". For indoor localization, we consider the IEEE802.11 WLAN environment. Generally, received signal strength indicator (RSSI) is used to obtain a specific position of the user under the WLAN environment. RSSI has a characteristic that is decreased over distance. To use RSSI at indoor localization, a mathematical model of RSSI, which reflects its characteristic, is used. However, this RSSI of the mathematical model is different from a real RSSI, which, in reality, has a sensitive parameter that is much affected by the propagation environment. This difference causes the occurrence of localization error. Thus, it is necessary to set a proper RSSI model in order to obtain an accurate localization result. We propose a method in which the parameters of the propagation environment are determined using only RSSI measurements obtained during localization.

• Journal of Electrical Engineering and Technology
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• 제12권3호
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• pp.1286-1291
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• 2017

In this paper, we propose an indoor positioning system that makes use of the attenuation model for IEEE 802.11 Channel State Information (CSI) in order to determine its distance from an Access Point (AP) at a fixed position. With the use of CSI, we can mitigate the problems present in the use of Received Signal Strength Indicator (RSSI) data and increase the accuracy of the estimated mobile device's location. For the experiments we performed, we made use of the Intel 5300 Series Network Interface Card (NIC) in order to receive the channel frequency response. The Intel 5300 NIC differs from its counterparts in that it can obtain not only the RSSI but also the CSI between an access point and a mobile device. We can obtain the signal strengths and phases from subcarriers of a system which in turn means making use of this data in the estimation of a mobile device's position.

• 한국위성정보통신학회논문지
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• 제10권1호
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• pp.56-61
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• 2015

본 논문에서는 사물인터넷(IoT, Internet of Things) 사용자가 안드로이드 플랫폼 기반의 홈 허브가 유니티 3D 모델링으로 사물인터넷 센서의 3D 위치표출 방안이 제안되었다. 특별히, 3차원 공간에서 IoT 센서는 설치 공간별로 클러스링을 통해 IoT센서 속성과 배터리 상태를 모니터링 방식을 설계한다. 또한, 3차원 공간상에서 신규 설치한 IoT 센서가 인접 센서들의 무선신호의 비콘신호 및 도착시간 분석에 따른 센서의 위치를 추적하는 방식은 센서의 무선신호세기(RSSI, received signal strength indicator)와 방위각을 기반으로 3차원 공간상에서 수신 각도에 따른 센서의 3D 위치를 표출할 수 있다. 이때 유니티 런쳐가 탑재된 스마트 허브 플랫폼은 사물인터넷 센서의 동작상태 모니터링이 가능하며, 다양한 센서의 생애주기를 관리할 수 있도록 동영상이 3차원 텍스쳐가 동시에 연동하도록 활용할 수 있다.

• 한국컴퓨터정보학회논문지
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• 제13권7호
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• pp.67-73
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• 2008

본 논문에서는 무선 센서 노드의 실내 위치 추적 시스템을 제안한다. 위치 추정에 사용하는 센서 값으로 RF 인터페이스의 수신 신호 강도 (RSSI)를 사용한다. 이동 노드를 부착한 사용자와 실내에 고정된 다수의 고정 노드의 신호 강도를 수신하여 사용자의 위치를 결정한다. 제안한 시스템은 측정에 의한 2.4GHz log-normal path loss 모델의 수신강도와 유클리드 거리 계산 방법과 신호 강도를 결합한다. 실험결과를 통해서 1.3m 이내의 오차로 위치를 추정함을 확인하였다.

• International Journal of Internet, Broadcasting and Communication
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• 제8권2호
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• pp.23-30
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• 2016

In this paper, for the pratical building envoronments, the propagation properties of the electromagnetic waves of the sub-1GHz bands, including the 447MHz, 868MHz, and 715MHz, and the 2.4GHz band are experimentally observed in therms of the received signal strength indicator (RSSI) value. The compasion of the frequency bands can be utilized to efficiently construct the wireless sensor networks (WSN) for the building automation control. In order to measure the RSSI values in the building, an RSSI measurement system is first designed, in which the master part can transmit data packets and measure the corresponding RSSI values, and the slave part can respond the received data packets. Using the measurement system, the RSSI values are then experimentally measured at four types of building enviroments. From the experimental result analysis, we could notice that the sub-1GHz, especially the 447MHz band, showd a good communication performance for the building environment and could provide an efficient WSN construction when the data rate is relatively low.

• 대한의용생체공학회:의공학회지
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• 제28권4호
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• pp.494-502
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• 2007

Ubiquitous location based services (u-LBS) will be interested to an important services. They can easily recognize object position at anytime, anywhere. At present, many researchers are making a study of the position recognition and tracking. This paper consists of postion recognition and user identification system. The position recognition is based on location under services (LBS) using a signal strength map, a database is previously made use of empirical measured received signal strength indicator (RSSI). The user identification system automatically controls instruments which is located in home. Moreover users are able to measures body signal freely. We implemented the multi-hop routing method using the Star-Mesh networks. Also, we use the sensor devices which are satisfied with the IEEE 802.15.4 specification. The used devices are the Nano-24 modules in Octacomm Co. Ltd. A RSSI is very important factor in position recognition analysis. It makes use of the way that decides position recognition and user identification in narrow indoor space. In experiments, we can analyze properties of the RSSI, draw the parameter about position recognition. The experimental result is that RSSI value is attenuated according to increasing distances. It also derives property of the radio frequency (RF) signal. Moreover, we express the monitoring program using the Microsoft C#. Finally, the proposed methods are expected to protect a sudden death and an accident in home.

• 한국철도학회논문집
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• 제19권5호
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• pp.585-591
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• 2016

최근 IoT환경에서 다양한 위치기반의 서비스의 확산으로 인해 실내측위는 중요한 영역으로 자리잡고 있다. 이에 본 논문에서는 특정 공간에 시설물, 서비스 등을 고려한 가상의 영역을 Zone으로 설정하였고, 다층퍼셉트론(MLP: Multi-Layer Perceptron)을 사용하여 Zone을 인식하는 방법을 제안하였다. 제안방법의 다층퍼셉트론은 입력으로 BLE(Bluetooth Low Energy) Beacon의 RSSI(Received Signal Strength Indicator)신호를 입력으로 활용하였고 현재 위치의 소속된 Zone을 출력하였다. 제안방법의 검증을 위해서 실제 역사와 유사한 크기의 실험환경을 구축하였으며 4개의 Beacon을 설치하였고 2개의 Zone영역을 설정하였다.

• Journal of Ubiquitous Convergence Technology
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• 제2권2호
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• pp.78-87
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• 2008

Received signal strength indicator (RSSI) is used as one of the ranging techniques to locate dynamic sensor nodes in wireless sensor network. Before it can be used for position estimation, RSSI values must be converted to distances using path loss model. These distances among sensor nodes are combined using trilateration method to find position. This paper presents an idea which attempts to integrate both path loss model and trilateration as one algorithm without going through RSSI-distance conversion. This means it is not simply formulas combination but a whole new model was developed. Several advantages were found after integration: it is able to reduce processing load, and ensure that all values do not exceed the maximum range of 16-bit signed or unsigned numbers due to antilog operation in path loss model. The results also show that this method is able to reduce estimation error while inaccurate environmental parameters are used for RSSI-distance conversion.